Machine learning, IoT bring big changes to data management systems

On a recent commute to TechTarget's Newton, Mass., office, I passed by an Apple Maps vehicle -- a white SUV topped with cameras and spinning light detection and ranging equipment that collects vast amounts of data about streets all over the world. I have a terrible sense of direction and rely on map apps more often than I'd care to admit -- so much so that Google Maps knows my routine inside and out. It proactively updates me on the time it will take to get from home to work or lets me know that I'm only 10 minutes from a Target store. I don't take for granted what a technological feat this level of personalization is; it requires massive amounts of data to be collected in real time, stored and validated before it can be put to use in a handy iPhone app. Commanding lakes of data Yet, with so many connected devices and widely available sensor technologies, access to data isn't the problem. Indeed, most companies are swimming in data. The real challenge is managing all that data and putting it to use. But once the hard part's ...